The present study is the first attempt to localize genomic regions that may harbor genes affecting human physical activity and inactivity levels. Promising evidence of linkage (P < 0.0023, detected in multipoint analysis) was found on one chromosomal region (2p22-p16). Suggestive linkages (P < 0.01) were also found with seven other chromosomal regions, among which regions 7p11.2 and 13q22 exhibited linkage with more than one physical activity phenotype. A genetic linkage is a property of a chromosomal locus, i.e., it can be used to identify chromosomal regions, which harbor genes and mutations affecting the phenotype. However, a significant linkage result provides no evidence regarding the contribution of a specific gene within the QTL to the trait variation. In the following paragraphs, we have provided a few examples of potential candidate genes located with the three QTL identified in the present study. We emphasize that these genes serve as examples only, and the chromosomal regions need to be investigated further using dense microsatellite mapping and positional cloning with single-nucleotide polymorphisms and linkage disequilibrium mapping.
The strongest evidence of linkage in the present study was observed for physical inactivity on chromosome 2p22-p16. The 20 cM region flanked by markers D2S405 and D2S2739 contains several potential candidate genes. A QTL for hereditary spastic paraplegia type 4 (SPG4) has been mapped on the same region (10,33). SPG4 is an autosomal dominant neurodegenerative disorder characterized by progressive spasticity of the lower limbs. The mean age of onset is 30 yr, but there is considerable variation in the age of onset and the severity of the symptoms. For example, Durr et al. (8) reported that 34% of the SPG4 gene carriers who were clinically affected (increased reflexes and/or extensor plantar responses) were unaware of the symptoms. SPG4 is caused by mutations in a gene encoding spastin (11), a member of the AAA family of ATPases, which is located about 1 Mb from the marker D2S2347. One could speculate that sequence variation at the SPG4 locus resulting in nonsymptomatic differences in neuromuscular controls could potentially influence the propensity to be physically inactive.
Other potential candidate genes on the region are striatin and member 1 of the solute carrier family 8 (Na/Ca exchanger 1). The striatin gene is located between markers D2S2347 and D2S2305, and it encodes an intraneuronal calmodulin-binding protein, which is expressed especially in the striatum and motoneurons (2). Inhibition of striatin by antisense oligodeoxynucleotides induced a significant decrease in nocturnal locomotor activity in rats (2). Na+/Ca2+ exchanger 1 is expressed mainly in myocardium and plays a vital role in the regulation of intracellular Ca2+ concentration in the cardiomyocytes. It removes excess calcium ions from the cell during relaxation and thereby facilitates the contraction-relaxation cycle of the myocardium. At this time, there are no data to support the contention that DNA variation in these genes could play a role on the sedentary to active continuum.
A suggestive linkage at region 13q22-q31 was found with both total daily physical activity and moderate to strenuous physical activity phenotypes. A gene encoding endothelin B receptor has been mapped on chromosome 13q22, and in rats endothelin B receptors have been shown to mediate the increase in spontaneous locomotor activity induced by treatment with a low dose of endothelin 1 (23). Moreover, the region 13q31-q34 has been previously linked with bipolar disorder, which is characterized by extreme swings in mood with occasional low activity level and lack of motivation (16).
Genome-wide linkage analysis can be used to identify chromosomal regions, which harbor genes and mutations affecting the phenotype, but a significant linkage does not indicate an association between the genetic marker and the trait of interest. Ideally, a replication of the QTL in other populations would be needed to further support the relevance of the chromosomal region for a given phenotype. Unfortunately, there are no previous linkage studies on physical activity levels in humans, and therefore the comparison of our findings with those from other populations is not possible. On the other hand, several QTL have been reported for locomotor activity in rodents (5,6,9,13,18,22,26–28,35). Using a human-mouse homology map (http://www.ncbi.nlm.nih.gov/Homology/), we checked whether the chromosomal regions detected in the present study match with those previously reported in mice. However, no such correspondence was found. We have previously reported several QTL for endurance training-induced changes in maximal oxygen uptake (4), submaximal exercise blood pressure (29) and stroke volume (30), and body composition (7) in the HERITAGE Family study. Comparison with the results of the present study reveals that physical inactivity QTL on chromosome 2p22-p23 does not really coincide with any of the training response QTL, although linkages with stroke volume and maximal oxygen uptake changes were detected with markers about 15 cM upstream and downstream, respectively, of the inactivity QTL. These results suggest that it is unlikely that level of physical activity and responsiveness to endurance training share a common genetic background.
One should recognize that physical activity phenotypes assessed from diaries and questionnaires have clear limitations. They are commonly used in population studies where their usefulness has been repeatedly demonstrated. Indeed, physical activity level assessed by these instruments has been shown to be associated with risk of hypertension, diabetes, coronary heart disease and mortality rates. Overall, we feel confident that the QTL identified in the present genomic exploration will eventually be proven to be of significance for human variation in physical activity level. It is even possible that the evidence for genomic loci contributing to inactivity or activity phenotypes may become stronger when similar studies can be performed with more direct phenotypic measures of activity.
The genetic dissection of complex traits represents a daunting challenge. A genomic scan with a set of highly polymorphic markers is a useful strategy to identify human chromosomal regions harboring genes of interest. In the present study, the QTL for the inactivity phenotype on 2p16-p22 was supported by a level of significance sufficiently strong to warrant further exploration with additional markers, such as single nucleotide polymorphism markers. The goal would be to refine the genomic region where the QTL resides in order to undertake positional cloning of the gene(s) involved. Our results also suggest that different genomic regions are linked with different activity phenotypes. This may indicate that different domains of physical activity (e.g., inactivity vs strenuous activity) are influenced by different mechanistic pathways and therefore different genes and genomic regions are detected for these traits.
In conclusion, the results of the present genomic scan support the hypothesis that there are genes contributing to the individual differences in levels of habitual physical activity. The identification of these genes should advance our understanding of the determinants of voluntary and spontaneous activity levels. It would be desirable to replicate such studies in other populations with the goal of defining whether some of the QTL observed here are common to other ethnic groups or if they are specific to some populations or given set of environmental conditions. New insights into the mechanisms underlying a sedentary or a physically active lifestyle can be expected in the long term from these and other genetic and molecular studies.
The Quebec Family study has been supported over the years by multiple grants from the Medical Research Council of Canada (PG-11811, MT-13960, and GR-15187). This study was also supported by grants from the Academy of Finland and the Finnish Ministry of Education for R. Simonen. C. Bouchard is partially supported by the George A Bray Chair in Nutrition. The results of this paper were obtained by using the program package S.A.G.E., which is supported by a U.S. Public Health Service Resource Grant (RR03655) from the National Center for Research Resources.
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